Generation, Transmission & Nat Gas Network Co-Optimizations

1. Generation, Transmission & Nat Gas NetworkCo-Optimizations Transparent, Repeatable, Defendable, and Published www.energyexemplar.com

2. Market Simulation & Analysis • Proven power and natural gas market simulation tool • Uses mathematical programming, optimisation and stochastic techniques (MIP, LP, SO) • Robust analytical framework: • Security Constrained Unit Commitment and Economic Dispatch • Stochastic Renewable Energy Models • Interregional Planning • Monte Carlo Simulation Risk and Reliability Analysis • Portfolio Optimization and Fuel Cost Minimization • Users can enable different co-optimizations for different cases • Power system model scalable to thousands of generators and transmission lines and nodes, or zonal or regional representations such as pipe and bubble Integrated Gas and Electric Model

3. PLEXOS Integrated Tools • Production Cost w/ Co-Optimization of Ancillary Services • Detailed nodal production cost or zonal (pipe and bubble) production cost with user settable time intervals from sub hourly, to hourly, daily, weekly, monthly, annual • Co-Optimization of Sub-Hourly Ancillary Services with Energy Market and Transmission Power Flows • Co-Optimization of Production Costs (nodal or zonal) Electricity Market and Natural Gas Network • Mid Term Co-Optimization • Annual or monthly constraints such as emissions or hydro decomposed to short term optimization of Production Cost • Long Term Planning Co-Optimization of Generation and Transmission Expansion as well Natural Gas Network Expansion • Chronological or Duration curve (nodal or zonal) Co-Optimization of Generation and Transmission and User can enable co-optimization of natural gas network expansion with transmission and generation expansion or fix generation and transmission expansion and elect to optimize the natural gas network to accommodate the generation transmission expansion scenarios. • The model optimizes using Mixed Integer Linear Programming (MILP) in which the transmission expansion and generation retirements are modelled as “integer” decisions to ensure full commissioning of transmission upgrades and full decommissioning of generating units in one particular year. Generation expansion is modelled using continuous variables, allowing partial power plants to be built in a particular year. • Reliability Evaluation • Convolution Method to calculate LOLEand LOLP and true Monte Carlo Simulation to consider transmission network and renewable generation uncertainty

4. Generation Characteristics Electrical Network Data Natural Gas Network Data Demand and Energy Shapes Fuel Prices Hurdle and Wheeling Rates Constraints Others Annual Environmental Constraints Energy Constraints Mid Term Optimizations Others Integrated Planning DatabaseIn PLEXOS Single Database Facilitates Multiple Types of Studies FOR Transmission FOR Generation FOR Gas Pipeline Renewable Variability and Uncertainties Demand Uncertainty Others Generator Costs Transmission Line Costs Pipeline Costs Gas Storage Costs Energy Efficiency Cost Curve Demand Shapes Others

5. PLEXOS Public Policy Applications

6. Transparent, Repeatable, Defendable, and Published • Transparent: • The LP formation is open to the PLEXOS user and software and datasets developed to ISO 9001:2008 Quality Control system and software commercial • Repeatable: • Developed Cases and Study Processes Can Be Transferred to Other PLEXOS Users • Defendable: • PLEXOS licensed in United States, Australia, Europe, Asia-Pacific, Russia, and Africa • PLEXOS Installation Sites: 136 • Countries PLEXOS Installed: 33 • PLEXOS Licenses: 769 • PLEXOS Users: 716 • Licensed by National Labs, ISO’s, Utilities, Generators, Regulators • Published: • http://energyexemplar.com/publications/ • http://energyexemplar.com/publications/research-publications/ Example PLEXOS Licensed Users MISO, CALISO, IESO, NBSO, AEP, SCE, PG&E, AEMO, RWE, OFGEM, National Grid UK, CEC, NREL, SANDIA, PNNL, LLNL